Exploring EFL learners’ perceived promise and limitations of using an artificial intelligence speech evaluation system for speaking practice

探索性研究 计算机科学 心理学 人工智能 自然语言处理 数学教育 社会学 人类学
作者
Bin Zou,Sara Liviero,Qing Ma,Weilei Zhang,Yiran Du,Peiling Xing
标识
DOI:10.31219/osf.io/ec68h
摘要

This study explores English as a Foreign Language (EFL) learners' perceptions of the promise and limitations of EAP Talk, an AI-based speech evaluation system, for speaking practice. Using a mixed-methods approach, data were collected from 366 EFL learners across five universities through questionnaires and semi-structured interviews. The findings reveal that EAP Talk significantly enhances speaking skills, including pronunciation, grammar accuracy, idea-organization, read-aloud, and presentation skills. Participants appreciated the convenience, motivational aspects, and institutional efficiency of EAP Talk, which allowed for flexible and autonomous learning. However, several limitations were identified. Issues with the accuracy of voice recognition and score feedback affected learners' confidence in the feedback. The relevance of practice materials to academic courses was another concern, as was the limited detail in the feedback provided by EAP Talk, which often lacked comprehensive explanations and corrective guidance. The absence of feedback on grammar accuracy and textual organization further limited the tool's effectiveness for developing comprehensive speaking proficiency. These findings suggest that while EAP Talk holds significant potential for enhancing language learning, ongoing improvements are necessary to address its limitations. This study contributes to the understanding of how AI tools can support EFL learners for speaking practice.
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